A Novel Multiple-Instance Learning-Based Approach to Computer-Aided Detection of Tuberculosis on Chest X-Rays Abstract?To reach performance levels comparable to human experts, computeraided detection < CAD > systems are typically optimized following a supervised learning approach that relies onlarge training databases comprising manually annotated lesions. However, manuall y outlining those lesions constitutes a dif?cult and time-consuming…
A Survey on Blood Vessel detection Methodologies in Retinal Images Abstract? Automatic detection of the blood vessels in retinal images is a challenging task. A survey has been made to help biomedical engineers and medical physicists. Here we have taken three different methods for blood vessels segmentation, method (a) a novel method to segment the…
Automated Vessel Segmentation Using Infinite Perimeter Active Contour Model with Hybrid Region Information with Application to Retinal Images Abstract? Automated detection of blood vessel structures is becoming of crucial interest for better management of vascular disease. In this paper, we propose a new in?nite active contour model that uses hybrid region information of the image…
Automatic localization and segmentation of optic disc in fundus image using morphology and level set Abstract? Optic disc (OD) localization and segmentation are important in developing systems for Automated diagnosis of various serious ophthalmic pathologies. A new, fast and robust methodology for fully automatic localization and segmentation of the optic disc in fundus images. This…
Four-Class Classification of Skin Lesions With Task Decomposition Strategy Abstract? Four-Class Classification of Skin Lesions With Task Decomposition Strategy. A new computer-aided method for the skin lesion classification applicable to both melanocytic skin lesions (MSLs) and nonmelanocytic skin lesions (NoMSLs). The computer-aided skin lesion classification has drawn attention as an aid for detection of skin…
-Lung Lesion Extraction Using a Toboggan Based Growing Automatic Segmentation Approach Abstract? Lung Lesion Extraction Using a Toboggan Based Growing Automatic Segmentation Approach. The accurate segmentation of lung lesions from computed tomography (CT) scans is important for lung cancer research and can offer valuable information for clinical diagnosis and treatment. However, it is challenging to…
On Efficient Feature Ranking Methods for High-throughput Data Analysis Abstract? On Efficient Feature Ranking Methods for High-throughput Data Analysis. Ef?cient mining of high-throughput data has become one of the popular themes in the big data era. Existing biology related feature ranking methods mainly focus on statistical and annotation information. In this study, two ef?cient feature…
On the Use of Coupled Shape Priors for Segmentation of Magnetic Resonance Images of the Knee Abstract? On the Use of Coupled Shape Priors for Segmentation of Magnetic Resonance Images of the Knee. Active contour techniques have been widely employed for medical image segmentation. Significant effort has been focused on the use of training data…
Prostate Segmentation in MR Images Using Discriminant Boundary Features Abstract? Prostate (i.e., gland located between the bladder and the penis) segmentation in magnetic resonance image i.e., technique used to image the body using discriminant boundary features. The prostate in magnetic resonance image has become more in need for its assistance to analysis and surgical planning…
Recognizing Common CT Imaging Signs of Lung Diseases Through a New Feature Selection Method Based on Fisher Criterion and Genetic Optimization Abstract? Recognizing Common CT Imaging Signs of Lung Diseases Through a New Feature Selection Method Based on Fisher Criterion and Genetic Optimization. Common CT imaging signs of lung diseases CISLs < Final Year Projects...
Rotation Invariant Texture Retrieval Considering the Scale Dependence of Gabor Wavelet Abstract? Rotation Invariant Texture Retrieval Considering the Scale Dependence of Gabor Wavelet. Obtaining robust and ef?cient rotation-invariant texture features in content-based image retrieval ?eld is a challenging work. We propose three ef?cient rotation-invariant methods for texture image retrieval using copula model based in the…
Segmenting Retinal Blood Vessels with Deep Neural Networks Abstract?The condition of the vascular network of human eye is an important diagnostic factor in ophthalmology. Its segmentation in fundus imaging is a nontrivial task due to variable size of vessels, relatively low contrast, and potential presence of pathologies like microaneurysms and hemorrhages.< final year projects >…
